loading data from a file
In the data source combo box, found in the Data source tab of the Group settings dialog box, the first item group is dedicated to loading data from a file existing on your system (local disk, removable disk or network location).
Once you have selected the type of file you want to load data from, by clicking the
button, you will be prompted with a standard Open file
dialog box that will enable you to select the file containing the data you wish the selected group to link to.
Once the file has been selected, enter all additional information required to access the data in the file, such as password or column information. For example, in case you're loading data from a Microsoft Access database file you will be able to enter the password if the file is password protected. If you're using an Excel file, you might want to define if the First line contains field names option.
In case the selected file supports multiple tables or worksheets, these will be loaded and listed in the center-screen combo box, after you have clicked the Load worksheets button (or Load tables, depending on the context). At this point you will be able to load the data using two different approaches:
- Select the table (or worksheet) you want to load data from, from the list of available tables.
- Select the last item "SQL...", and enter a SQL query to be executed against the selected data source (for advanced users).
The query result will depend on the type of data source selected. The query must be a SELECT query and must comply with the SQL implementation supported by the data source.
Connection to the underlying data source is always a read-only connection and the source data can never be modified by Labeljoy.
If the query cannot be executed, an error message will be shown.
On the web, many sites offer resources that can help you learn and write basic SQL queries. Here's a few helpful links:
The amount of data loaded may decrease system performance when large data sources are used. To ensure that Labeljoy keeps memory usage within an acceptable range, it is advisable to avoid loading entire tables containing hundreds of thousands of records. Depending on your system performance, it is suggested to avoid loading data sources larger than 10,000 records whenever possible